In MITSloan Management Review Article “A Plan to Invent the Marketing We Need Today”, Yoram Wind wrote

This world has led to a new breed of consumers. They expect customization (make it mine), communities (let me be a part of it), multiple channels (let me call, click or visit), competitive value (give me more for my money) and choice (give me search and decision tools).

In this post I would like to focus on the combination of the first (customization) and the last (choice) and call it “personalization” for the purpose of this discussion.

As a consumer selecting a product to purchase, I rely on marketing collateral to form my expectations, and on the comments of my peers who already experienced the products I consider to buy. Any decision is made with a relative shortage of information required to make this decision. An unavoidable ambiguity of available information from marketing collateral and product scores from online retailers or advertisers, does not help the consumer to reduce uncertainty of their decision easily. I want to know how likely this product will satisfy me, because while I know that other customers, who described their experiences are my peers, their product scores do not help me to understand whether we share and value the same aspects of a product experience. The only way to figure that out is to read carefully the descriptions of their experience. That takes a lot of time and effort.

The higher number of customer reviews and more detailed their description of a product experience (more data), the more useful and accurate are the results of personalized information to support the purchasing decision.

The key element for me, as a consumer, is the reliability issues of the Garmin product when it is compared to very similar Magellan GPS. These reliability reputation issues are not “visible” looking at traditional 4.5 stars customers gave to Garmin. However for me reliability of GPS device represent the highest differentiator, and allows me to “personalize” my choice.

A very similar problem facing marketeers who want to understand specific, personal characteristics that affect the reputation of their products and brands, and how they influence their competitive position in their market segments. Their problem is multiplied by a number of products, brands and competitors they have to follow and lack of consistent methodology to produce effective output. The technologies are complex to implement and costs are staggering.

Professor Wind continues

Through its maturation as a discipline over the past half century, marketing has emerged as a rigorous field. Tools such as conjoint analysis, economic and econometric modeling, behavioral economics, data mining, and techniques derived from mathematical psychology have raised the level of rigor and strengthened the insights that marketing can contribute to the enterprise. But many of the most rigorous tools were developed years ago. Today’s challenge is how to move from using old tools that are focused on solving problems of the past to developing new and rigorous tools that are relevant to the challenges of today and the future.

I would like to pose that “personalization” is the new “segmentation”, and certain aspects of personal Customer Experience provide a lot more guidance for marketers than demographics, ethnicity, etc. because they are much closer correlate to  how your customers use and experience your products in their circumstances.

Marketing is divided between behavioral and quantitative approaches to marketing questions. Increasingly, the recruitment of faculty and doctoral students, and the design of workshops, are focused separately on behavioral and quantitative approaches. Ideally, the
two sides should come together. Markets can be seen through either a behavioral or quantitative lens, but as with binocular vision, we gain more depth when we look through both.

I found an interesting post by Jeffrey Henning today. The article is touching on emotional attachment people have for different measurement  scales used in Market Research. I can see how easily it come into play as we try to find one method to fit variety of research projects. Every method or tool has it’s limitations and therefore the challenge is to find the most appropriate one for the task at hand. Jeffrey quotes Brad Borther who provides an excellent advise:

Ten-point scale: “A five-point scale is totally inappropriate for customer satisfaction studies. Why? It lacks enough granularity and robs companies of a burning desire to take corrective action. It commonly leads executives to believe that ‘80% rate us four or five; that’s great, let’s move on,’ without realizing that it simply means that 80% are at least somewhat satisfied. Further, many people will never rate anything a ‘five,’ resulting in ‘four’ including those who are really very satisfied and those who are only somewhat satisfied. To avoid this topping effect, use at least a 10-point scale and count nine and 10 ratings as fully satisfied. This will also allow easier analysis of what bottom-line effects satisfaction has, since such tools as regressions work better with a more granular score.” – Brad Bortner, principal analyst with Forrester Research, “Best Practices: Why Customer Satisfaction Studies Fail“

Since our approach to measuring Product Reputation (delta between Customer Expectations and Customer Experience) is focused on competitive position of multiple products within their category, and our method does not require to ask people to measure it,  I have decided to use “0″ to “2″ balanced scale with 2 decimal points for more granularity. It is interesting how infrequently people want to challenge a value of our methodology or accuracy of our analysis, compared to the selection of the measuring scale. By now I gave up any attempts to change their mind. We arrive to the scores using our algorithms to analyze Customer comments and reviews, not by asking them to measure according to any scale, therefore is much easier for us to recalculate Product Reputation scores to appear in a customer “favorite” scale. The integrity of the finding is not compromised by the conversion.

I wish all religious wars could be settled that easily.

The input and collaboration of many creates value in most cases, but probably not in all. One of the best examples of  the concept of “crowdsourcing” is Wikipedia, but there are some troubling signals that have come out of this social experiment:

More than 49,000 editors left Wikipedia’s English-language edition during the first three months of 2009, compared with only 4,900 for the same quarter a year earlier, according to the Journal, quoting Spanish researcher Felipe Ortega, who analyzes Wikipedia’s online data. Though the service still boasts about 3 million active contributors, volunteers are leaving more rapidly than new ones are joining, the Journal said.

I fancy myself as being relatively well informed, and have joined, as a volunteer a few months ago, but upon reflection saw nothing particularly valuable to contribute to the existing entries. How many in a “crowd” makes “crowdsourcing” meaningful?

Wikipedia co-founder Jimmy Wales discussed the site in an interview with Silicon.com earlier this month. With 13 million articles now written and edited by volunteers, Wales sees conflict among multiple contributors as the exception.

“We really tend to use less inflammatory words–try to stick to basic facts and so on. And that’s come about over time. You have people come together [on Wikipedia] with different viewpoints but in general they tend to be trying to work in good faith to collaborate and compromise with other people.”

Wales also pointed out that most articles are written by a small number of people.

“One of the things that’s important to know about Wikipedia is that the entries that are edited by hundreds of people are really anomalies,” he told Silicon.com.

So at what point does the wisdom of the crowd turn into madness of the mob? I am not envious of Wales as he seems to manage as explosive a process as nuclear fusion, when it comes to the emotions and egos involved, but I am very grateful that he does, as many studies have shown that Wikipedia’s authority is every bit as high, if not higher, than one of traditional encyclopedias. The accuracy is the context in which authority of an encyclopedia is judged.

The debate about the comparative accuracy of Market Research methods (online vs telephone) made me think about the context in which this debate is formed.

The debate over the accuracy–and quality–of survey research conducted online is flaring at the moment, at least partly in response to a paper by Yeager, Krosnick, Chang, Javitz. Levendusky, Simpson and Wang: “Comparing the accuracy of RDD telephone surveys and Internet surveys conducted with probability and non-probability samples.”

In my opinion the methods employed to conduct the research are secondary to the findings, the researcher attempts to discover. This opinion usually draws very heated arguments from purists who are concerned that “biases” cannot be avoided if the research is “tainted” by pre-conceived expectations. I totally agree – biases cannot be avoided, or even tried to. Without biases the results of research is meaningless and it is a lot more useful to introduce the power of the context and some structure into the process.

Meaningful, representative and actionable results of market research are more important than its marginal accuracy.